EchoGo Heart Failure (2.0)

K240013

Ultromics Limited · cleared 2024-09-23 · product code QUO · Cardiovascular

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.8)
“Yes”
Algorithmartificial intelligence (AI) model developed using a convolutional neural network
source quote (p.7)
“The output of both devices is based on an artificial intelligence (AI) model developed using a convolutional neural network that produces a classification result.”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.10)
“Post-market Management of Cybersecurity in Medical Devices. Content of Premarket Submissions for Management of Cybersecurity in Medical Devices. Cybersecurity for Networked Medical Devices Containing Off-the-Shelf (OTS) Software: Guidance for Industry.”

Validation studies (1)

Retrospective clinical

n=1,578 patients · 8 site(s)

endpoints: sensitivity; specificity; accuracy; repeatability; reproducibility

standards: ISO 14971:2019, IEC 62304:2015, IEC 62366-1:2020, NEMA PS 3.1 - 3.20 2021e, IEC ISO 10918-1:1994, ISO 14155:2020

Reported performance (3 observations)

sensitivity90.3CI 95% CI: 88.5, 92.4%
source quote (p.15)
“This equated to a sensitivity of 90.3% (95% CI: 88.5, 92.4%) and a specificity of 86.1% (95% CI: 83.4, 88.3%) when removing the no classification studies from the calculation, as per the intended use of the device.”
specificity86.1CI 95% CI: 83.4, 88.3%
source quote (p.15)
“This equated to a sensitivity of 90.3% (95% CI: 88.5, 92.4%) and a specificity of 86.1% (95% CI: 83.4, 88.3%) when removing the no classification studies from the calculation, as per the intended use of the device.”
aurocas written: “auc”0.947CI 95% CI: 0.934, 0.958)
source quote (p.16)
“The area under the receiver operator characteristic curve (AUROC) was 0.947 (95% CI: 0.934, 0.958) when removing no classification studies, and 0.937 (95% CI: 0.924, 0.949) when considering all studies and ignoring uncertainty and instability metrics.”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Cardiovascular panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K240013